arXiv論文 M.Imaizumi, K.Fukumizu, “Deep Neural Networks Learn Non-Smooth Functions Effectively”, http://arxiv.org/abs/1802.04474 の説明スライドです。
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By the XLA team within Google, in collaboration with the TensorFlow team One of the design goals and core strengths of TensorFlow is its flexibility. TensorFlow was designed to be a flexible and extensible system for defining arbitrary data flow graphs and executing them efficiently in a distributed manner using heterogenous computing devices (such as CPUs and GPUs). But flexibility is often at od
Gradient boosting (GB) is a machine learning algorithm developed in the late '90s that is still very popular. It produces state-of-the-art results for many commercial (and academic) applications. This page explains how the gradient boosting algorithm works using several interactive visualizations. Decision Tree Visualized
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